Adaptive network querying system

ABSTRACT

The systems and methods of the invention provide a network querying or content system which drives high relevance question sets or content to users and presents it in the optimal template to ensure user interaction. In accord with at least one aspect, the system assesses the context (of a user) by interpreting the optimal template based on personality mapping of the user and relevancy mapping of the query or content. In a technically efficient manner, the system employs client-based managers and builders to select, supplement, or build user profiles and user interface templates to optimize queries or content based on a user&#39;s present profile. The systems and methods of the invention perform processing, in a technically efficient manner, to assess question or content set interaction and relevancy to generate targeted question sets or content that encourage overall user health and wellness.

RELATED PATENT APPLICATION

The present application is a continuation of and claims priority to U.S.patent application Ser. No. 16/125,985 filed Sep. 10, 2018 entitled“Adaptive Network Querying System”, the content of which is incorporatedherein by reference in its entirety; this application and U.S. patentapplication Ser. No. 16/125,985 claims priority to U.S. patentapplication Ser. No. 15/943,309 filed Apr. 2, 2018, the content of whichis also incorporated herein by reference in its entirety.

FIELD OF THE INVENTION

This present invention relates to the field of adaptive networks andmore specifically to adaptive network systems for smart querying ofusers.

BACKGROUND OF THE INVENTION

Current technological environments, various services, user deviceapplications and other platforms send queries or surveys to users basedon the goals of the questioner and/or in some predetermined scheduledstyle or manner, for example.

These current query systems are designed to send questions to usersuncertain if the user will see, interact with, or answer any of thequeries. However, this leads to inefficiencies as queries are often sentwithout interaction, sent multiple times, and often with little responseor questionable accuracy and relevancy. The current inefficient systemsnot only clog networks with multiple and redundant queries, they alsoclog the user's equipment such as mobile phones, docking systems likein-dash vehicle displays, voice activated equipment, laptops and smartwatches; consume excessive power of the user's varying equipment and thenetwork, consume bandwidth, and make the user disinterested in furtherqueries. These inefficiencies cost both the provider and user.

Therefore, technical improvements and solutions are needed to overcomethese technical problems while accommodating the evolving needs ofusers. The systems and methods of the present invention provide suchimprovements.

SUMMARY OF INVENTION

The present invention provides a network querying system and methodwhich drives high relevance question sets to users and presents it inthe optimal template to maximize user interaction. The system assessesthe context (of a user) by interpreting the optimal template based onpersonality mapping of the user and relevancy mapping of the query orcontent. The system employs client-based managers and builders toselect, supplement, or build user profiles and user interface templatesto optimize queries based on a user's present profile in a technicallyefficient manner. The systems and methods of the invention performprocessing, in a technically efficient manner, to assess question setinteraction and relevancy to generate targeted question sets thatencourage overall user health and wellness.

The present invention also provides a system of networked apparatusesthat provide adaptive queries, with the processing being performed overa network which provides a communication interface amongst the networkedapparatuses, each of the apparatuses in the form of a tangibly embodiedcomputer processor, each computer processor including instructions on anon-transitory computer memory. The system comprised of: the networkover which a plurality of networked apparatuses communicate; an adaptivequery server, the adaptive query server including: a query processorincluding instructions on a non-transitory computer medium, thenon-transitory computer medium constituted by one or more data storagemediums; the query processor including a training manager module forloading at least one query; the query processor including a personalitymapping module for mapping at least one recipient profile to create arecipient profile file for each individual recipient associated with theplurality of networked apparatuses, the recipient profile file stored inthe one or more data storage mediums; the query processor including arelevancy mapping module for mapping the relevancy of the one or morequeries to a plurality of individual recipients associated with theplurality of networked apparatuses; the query processor determining aquery for a selected recipient based on the recipient profile fileassociated with the recipient and the relevancy mapping of the query;the query processor generating a query message including data on thequery, the selected recipient profile, and a suggested recipientinterface template; and the query processor initiating a communicationincluding the query message to at least one recipient device associatedwith the selected recipient. The system further including at least onerecipient device, with the recipient device including: an adaptiveprocessor including instructions on a non-transitory computer medium,the non-transitory computer medium constituted by one of more datastorage mediums; the adaptive processor including a profile module fordetermining a real time profile of the recipient associated with therecipient device and storing the profile in one of the data storagemediums on the device; the adaptive processor processing the querymessage to extract the query, the selected recipient profile, and thesuggested recipient interface template; the adaptive processor comparingthe selected recipient profile from the adaptive query server to theprofile file on the recipient device; the adaptive processor including aprofile manager and selecting a final recipient profile from a pluralityof recipient profiles stored in the one or more data storage mediumsbased on the comparison; the adaptive processor including a userinterface manager, the user interface manager selecting a final userinterface template from a plurality of user interface templates storedin the one or more data storage mediums based on the final user profile;and the adaptive processor generating a user interface for display onthe recipient device comprised of the final user interface template, afinal set of query data from the plurality of query data and selectingthe location of each element of the final set of query data within thefinal user interface template.

In addition, the query message may include a file with a filename, andthe filename includes attributes for initial profile screening by therecipient device. The query message may also include a file with thecontent of the file including a plurality of attributes for profilescreening by the recipient device. The profile module may create a newprofile when the recipient's activities indicate one or more traits oractivities inconsistent with the profile or profiles stored on thedevice. The user interface module may create a new user interfacetemplate when the final user profile is inconsistent with the userinterface template or templates stored on the recipient device. Theadaptive processor may modify the query based on the final user profile.The query data may include images, and the adaptive processor may selectimages for use in the final user interface based on the final userprofile. The recipient profile may be a personality profile or one ofthe other profile types or categories identified herein

The present invention also provides a method for dynamically adaptingand displaying at least one query on a recipient device within a networkof networked devices, the method comprising: (1) mapping, by a queryprocessor device in communication with the recipient device, a recipientprofile against a set of known profiles; and the relevancy of the atleast one query to the recipient profile associated with the recipientdevice; (2) dynamically selecting, by the query processor, a query fromthe at least one query based on the recipient profile and the relevancymapping to transmit to the recipient device; (3) generating, by thequery processor, a query message including a plurality of query dataincluding a plurality of attributes on the at least one query, asuggested query format, the suggested recipient profile, and a suggesteduser interface template; (4) transmitting, by the query processordevice, the query message to the recipient device; (5) analyzing, by anadaptive processor on the recipient device, the query message andidentifying the plurality of attributes; (6) comparing, by the adaptiveprocessor, the plurality of attributes associated with the suggestedrecipient profile against a set of known profiles on the recipientdevice; (7) selecting, by the adaptive processor, a real-time recipientprofile; (8) determining, by the adaptive processor, a final userinterface template based on the suggested user interface template andthe real-time recipient profile, the determining including selecting aninitial user interface template from a plurality of templates on therecipient device; and (9) generating a user interface for display on therecipient device comprised of the final user interface template, a finalset of query data from the plurality of query data and selecting thelocation of each element of the final set of query data within the finaluser interface template.

The method further including inserting within the query message a fileand generating a filename for the file, the filename includingattributes for initial profile screening by the recipient device.Further, the method could include inserting a plurality of attributeswithin the file associated with the recipient profile and the suggesteduser interface template. The method further including generating a newprofile when the recipient's activities or interaction indicate one ormore traits (i.e. personality) are inconsistent with the at least oneprofile stored on the recipient device. The method further includinggenerating a new user interface template when the final user profile isinconsistent with the user interface template or templates stored on therecipient device. The method further including modifying the query basedon the final user profile. The method further including selecting imagesfor use in the final user interface from the set or query data, based onthe final user profile. Where the recipient profile being a personalityprofile or one of the other profile types or categories identifiedherein.

The present invention also provides a device for dynamically adaptingand displaying at least one query, comprising; a processor includinginstructions on a non-transitory computer medium, the non-transitorycomputer medium constituted by one or more data storage mediums. Theinstructions, when executed by the processor configures the recipientdevice to: receive at least one query message with a plurality of querydata and analyzing the query message to identify a plurality ofattributes; compare at least one of the attributes from the plurality ofattributes from the query message with a user profile or profiles (orattributes of a profile) stored on the device; select a real-time userprofile; determine a final user interface template based on thereal-time user profile, the determining including analyzing a pluralityof templates stored on the device using the selected real-time userprofile and then selecting the final user interface template; andgenerate a user interface for display on the device comprised of thefinal user interface template, a final set of query data from theplurality of query data; and selecting the location of each element ofthe final set of query data within the final user interface template.The query message may include a file with a filename, the filenameincluding attributes for initial profile screening by the recipientdevice. The query message may include a file with the file including aplurality of attributes for profile screening by the recipient device.The profile module may create a new profile when the recipient'sactivities indicate one or more traits inconsistent with the profile orprofiles stored on the device. The adaptive processor may modify thequery based on the selected real-time user profile. The real-time userprofile may be a personality profile or one of the other profile typesor categories identified herein.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention can be more fully understood by reading thefollowing detailed description together with the accompanying drawings,in which like reference indicators are used to designate like elements,and in which:

FIG. 1 depicts a high-level system diagram of an illustrative embodimentof the present invention.

FIG. 2 depicts a more detailed system diagram of an illustrativeembodiment of the present invention.

FIG. 3 depicts a flow diagram utilized by an illustrative embodimentemployed by the present invention.

FIG. 4 depicts a flow diagram of the query trainer aspects of anillustrative embodiment employed by the present invention.

FIG. 5 depicts an additional flow diagram including relative inputs ofan illustrative embodiment of the present invention.

FIG. 6 depicts an illustrative flow diagram for query refinement basedon relevancy and personality mapping of the present invention.

FIG. 7 depicts a system diagram of the multi-manager system of anillustrative embodiment of the present invention.

FIG. 8 depicts a system diagram of the client-side system of anillustrative embodiment of the present invention.

FIG. 9 depicts a system diagram of the profile manager and UI manager ofthe client-side system of an illustrative embodiment of the presentinvention.

FIG. 10 depicts a system diagram of the client side and server-sidemanger interaction of an illustrative embodiment of the presentinvention.

FIG. 11 depicts a flow diagram of the query messaging and client-sideprocessing employed by the present invention.

FIG. 12 depicts the user interface assembly elements of the presentinvention.

FIG. 13 depicts a flow diagram of the improved messaging of the presentinvention.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

Hereinafter, aspects of the methods and associated systems in accordancewith various embodiments of the invention will be described. As usedherein, any term in the singular may be interpreted to be in the plural,and alternatively, any term in the plural may b e interpreted to be inthe singular. It is appreciated that features of one embodiment asdescribed herein may be used in conjunction with other embodiments. Thepresent invention can be more fully understood by reading the followingdetailed description together with the accompanying drawings, in whichlike reference indicators are used to designate like elements.

As seen in FIG. 1, the present invention provides a system 10 whichincludes a server or cloud-based system 1 with local and remote storagecapabilities. The server system 1 builds a personalized model 2 for eachrecipient based on the measured relevancy 3, measured behaviors 4, andthe recipient's profile 5 related to a queries or content model 6. Thesystem 10 analyzes the queries model 6 as a function of training 7 thathas been provided to the system 10. The system 10 also includes one ormore client devices 13 running one or more software applications. Theclient device 13 communicates with the server through one or morecommunication paths or links 12. The software application 13 works withthe server-based system 1 to build and present a personalized query 14based on the question and answer creation 15, presentation andinteraction logic 16, and machine learning 17.

Through use of a myriad of known and captured data, training, varyingreal-world sensors, recipient interaction, and personality data andanalysis, the system determines relevancy, continuously adjusts, andbuilds a real-time user or personality profile of the recipient orrecipient of querying endpoints. The real-time personality profile isthen used to select, adjust, or build the style and wording of thecontent or query and presentation or graphical user interface of thecontent or query to the recipient.

The various data elements and attributes used by the system 10 includesbut is not limited to: curriculum training; personalization data;self-categorization data; traits and psychological data; physicalproperty and ownership data; demographic data; geographic data;environmental data; physiological data; genomics data; behavioral data;activity or interactivity data; and economic data.

Curriculum training is data and content from any breadth of query,question or content, from recall and reproduction orientated queries orcontent which can generate quick or easy responses, to skills andconcepts queries or content where the individual has detailed knowledgein a specific area like targeted health related queries, to queries orcontent relying on neural and cognitive reasoning networks forpredictive modeling and machine learning that can be queried in avariety of ways resulting in a variety of answers or reactions. E.g.Recall related: What is your favorite color? Which could be a colorpalette selection. E.g. Skill related: Have you ever had a headache thatwas so bad that you were nauseous? Which could be a yes/no response.E.g. Neural and Cognitive reasoning related: Do you feel better in thesunlight?

Questions or content may be responded to using varying approaches, bothdirectly and indirectly through inferring or through facial and audiorecognition. Responses or reactions could also include images foranswers, written response, additional sensor related data or multiplechoice for instance. Responses may require the user to manually selector enter an answer. However, the response to queries are not limited torecipient interaction with the device interface. The recipient may alsorespond or react using voice, which the system can analyze not only forthe word choice but also the frequency and tone used as a response.Further, the voice and its frequencies or signal can be analyzed to helpdetermine the proper profile to use to ensure maximized query setparticipation. The recipient may further respond through an action thatthe device or a secondary device, such as a camera, detects. Forexample, the system might respond to device motion, a head nod or shake,or a thumbs up or down gesture. Responses may also be given throughfacial recognition to answer the query or to determine or assess therecipient's mood.

Personalization data is used to build a recipient or user profiles. Therecipient profile is based upon: personality type, genderidentifications, demographics, common locations, ownership, measuredenvironment, measured physiology (i.e. vitals and genomics), measuredactivities (i.e. tasks), measured economy, measured behavior andrelevancy.

Personality type data may include percentage complete, and other factorsdetermine whether the system needs to further adapt the personality typeusing queries structured on common psychological methods for determiningunique traits and considerations (e.g. OCEAN, versus Myer Briggs orother options). Personality type could be inferred through interaction.For example, the system 10 might determine the initial personality typebased on whether or if the individual asks a lot of questions duringconsent, assuming they are going to a real individual, perhaps throughemail or some other means. Personality information can be inferred byhow somebody wants their data to be used (i.e. just for themselves orfor the betterment of society and population health). A myriad ofquestions and responses during setup and early interaction can be usedto determine an initial or baseline personality profile. The profile canbe modified, or new profiles created, based on a myriad ofcircumstances. Such might include time of day, day of the week, time ofyear, environmental or world events, or personal events and issues. Eachof the questions and interaction can be used, and even required, to mapto a personality through the sampling of data throughout the system.

Measured demographics data may include data regarding age, race, genderidentification, affinity, ethnicity, number in household, income,military status, country of birth, citizenship, educational level,education status, marital status, pregnancy status, job position.

Measured location data may include data related to home location(primary or secondary), commitments (appointments, planning), officelocation (single or multiple), real-time location, location of friendsand family members (living and deceased), and travel related location(vocational commuting, avocational, vacation).

Measured ownership data may include data related sources that areadjunct and available as classifiers and associated reasoning tobehaviors (classes, memberships), financial influence (cars, homes),emotional and sentimental items (generational, memorable) and locationidentifiers (time, coordinates).

Measured environment data may include many sensing elements such as:weather sensors, sound sensors, particle sensors, gas sensors, lightspectrum-heat detecting sensors, network analyzer sensors, radiocommunication analyzer sensors, magnetometer sensors, opticalcommunication sensors, proximity detection sensors, position -movementsensors, and usage sensors. The weather sensors may use or sense lightdetection, temperature, atmospheric pressure (barometric), and capturingposition of the sun and moon; sunrise and sun set; and local currentweather measurement which can be augmented with regional, national, andglobal data. The sound sensors can be used to detect noise level,frequency identification, and transcriptive services to name a few.Particle sensors may be used to detect or measure dust particles andpollen level using particulate matter and low pulse occupancy (LPO), andsmoke and mold spores by means of negative ion generator, orphotoelectric light detection. Gas sensors may be used to detect gas orfumes which might have a detrimental (or positive) effect including:formaldehyde (Molecular Formula: H₂CO or CH₂O); alcohol vapor (MolecularFormula: hydroxyl group-OH, e.g. Isopropyl-C₃H₈O or C₃H₇OH as well asEthanol-C₂H₆O or C₂H₅OH); benzene (C₆H₆); Hexane (C₆H₁₄); LiquefiedPetroleum Gas (LPG) which could include a mixture of butane (MolecularFormula: CH₃CH₂CH₂CH₃ or C₄H₁₀) and isobutene (Molecular Formula:(CH₃)₂CHCH₃ or C₄H₁₀ or (CHC₄H₁₀)₂CHCH₃); propane (Molecular Formula:CH₃CH₂CH₃ or C₃H₈); natural coal or town gas which could consist ofmethane or natural gas (Molecular Formula: CH₄); carbon dioxide(Molecular Formula: CO2); hydrogen (Molecular Formula: H₂); carbonmonoxide or possibly smoke (Molecular Formula: CO); and oxygen(Molecular formula: O₂). Light spectrum-heat detecting sensors can beused to detect various environment aspects including: visual-lightlevels; movement; heat maps; light spectrum identification; infrareddetection; UV radiation; and image recognition. Network analyzer sensorscan be used to detect various network aspects including: availablewireless networks; proximity; signal strength-RSSI; manufacturerinformation; serialization, addressing; standards-Wi-Fi, Bluetooth,Cellular; topology-MESH, Star, ring, point-to-point, bus, tree, hybrid;and network types (PAN, SAN, CAN, LAN, MAN, WAN, GAN). Radiocommunication analyzer sensors may be used to sense or detect: radiocommunication frequency; signal strength; active broadcasters; band (AM,FM, longwave, shortwave). Magnetometer sensors may be used to sense ordetect: magnetic field-inductive sensing of polarity, multi-axis fieldstrength detection, near-field communication (NFC). Opticalcommunication sensors may be used to sense or detect: 3-dimensionalpositioning of sensing emitter, signal strength of emitter or emitters,and communication. Proximity detection sensors may be used to sense ordetect radio signal strength feedbacks, light feedback, step responses,reactivity to nearby electro-magnetic objects and thermal heat placementto determine proximity of the recipient or devices. Position movementsensors may be used to detect or sense movement including: localposition; altimeter-elevation; gravitational force; movement relative toa 3-axis accelerometer; degree of change; speed of change; and globalpositioning systems (“GPS” for determining global longitude, globallatitude, global degree of change, global speed of change). The systemmay also employ usage sensors to detect usage such as electricity forindividual appliances or outlets, and total electricity used, activeoutlets versus inactive outlets, garage door usage, open or closeddoors, water leak detection, water usage, open or closed windows, cardistance traveled, car operating or car off, garbage empty or garbagefull, natural gas, LPG, petroleum gas, water return/waste, phone andinternet usage.

Measured physiological data including vitals and genomic data mayinclude many sensing elements such as: temperature sensors, heart ratesensors, pulse rate sensors, respiratory sensors, blood pressuresensors, metabolic sensors, circulatory sensors, neuro sensors, cardiacsensors, nerve sensors, pain response sensors, awake/sleep sensors, andhealth context sensors. Temperature sensors may be used to collectinternal, surface level, and external temperature. Heart rate sensorsmay detect, or sense heart rate and heart signal characteristics basedon the heartbeat and/or derived from an electrical impulse within theQRS signal. Pulse rate sensors may be used to detect, measure, or sense:the blood flowing through the circulatory system using a circulatorybased sensor like Blood Pressure or a Pulse Oximeter; or collectingblood flow transit time rate in conjunction with a QRS signal oradditional circulatory sensors (per location on the body). Respiratorysensors may be used to collect respiratory-breathing rate, positiveairway pressure to the lungs, physiological signal of forced expiratoryvolume, and forced vital capacity. Blood pressure sensors may be used tomeasure and collect degree of stress, degree of arteries constricted(vasoconstriction), white coat syndrome, medication influenced, exerciseinfluence, and resting state. Metabolic sensors may be used, includingblood glucose sensors, to collect blood sugar levels, metabolismbefore/after meals, detoxification influences, and sleeping influences.Circulatory sensors may be used to detect or sense pulse oximetry as anindirect measure of oxygen saturation (SpO₂), a direct collection ofarterial blood gases (SaO₂), partial pressure (PaO₂), tissue oxygensaturation (StO₂) and other O₂ data collection sites within the body,signal strength, and photoplethysmography (PPG). Neuro sensors may beused, including using EEG-brain sensors, to collect stress indicators,sleep indicators, and disorders. Cardiac sensors may be used, includingusing ECG, to collect heart activity, electrical impulses, QRS, and R-Rinterval. Nerve sensors may be used, including sensing the vagus nerve,and collecting resting state of the body's organs measured using vagaltone, and respiratory sinus arrhythmia (RSA). Pain response sensors maybe used, including collecting salival level of cortisol, to determinepain and stress (measured for example using pain level combined withvagal tone, RSA, blood pressure and heart rate). Awake and sleep sensorsmay be used to collect, and measure awake and sleep data including theenvironmental impact (e.g. movement, audible indicators-snoring, teethgrinding, sleep talking) combined with vitals (e.g. EEG—providing cortexactivity, NREM, REM, sleep depth; ECG-providing Heart rate changes;Respiration-changes, CPAP detection) and sweating (e.g. bodytemperature, perspiring and rate of perspiration). Health contextsensors may be used to determine various health conditions includingweight sensors, height through lift sensors and light detection, skinpigmentation and hair color through camera and light frequencydetection, dry skin rating via electrical conductivity, dry tongue viaelectrical conductivity, eye dryness via camera data collection, hearingtests, and coughing via audio recording.

Measured activity data may include many sensing elements such as: foodsensors, bathroom sensors, personal product sensors, shock sensors,daily task sensors, exercise sensors, travel sensors, appliance sensors,relaxation sensors, and hardware usage sensors. Food Sensors may includecaloric sensors, gluten detection sensors, meal detection sensors todefine, sense, or measure eating-nutrition, calories, meal status.Bathroom sensors may include using environmental usage sensor(s) ofelectricity, water and waste suggesting using the bathroom, toilet, orshower. Personal product sensors may sense or collect data on using atoothbrush sensor for brushing teeth, movement sensors connected tomakeup or hairbrush for detecting combing hair, and feedback productslike electrical stimulation for managing habitual needs (shock sensors).Daily task sensors may be used for sensing or collecting data on using acalendar, email activity, call activities suggesting working-busy day,light work day, planning to leave early/late, planning to arriveearly/late, needing to focus-do not disturb; meetings-presenter,decision maker, note taker, passive listener; conversations-deeplyengaged, or mildly listening; chores-mowing, auto services, homeservices, and personal services (purchases, healthcare checkups, dentalcheckups, physical and mental health-chiropractic, massages,acupuncture, therapist, community groups). Exercise sensors may be usedto sense or collect data including equipment reporting-workout time,intensity, calories burned, energy level, and category includingweights, cardio, and yoga. Travel sensors may sense or collect data fromemails, travel applications, environment sensors detecting indirecttraveling (i.e. someone else is doing the work), and direct traveling(i.e. driving, cycling, rowing, running). Appliance sensors may be usedto detect or sense using fridges and ovens to describe level ofcooking-status as engaged, lightly engaged, not engaged; or using theclothes washer, clothes dryer, dishwasher for chores detection alongwith increased water usage and electricity changes. Relaxation,meditation and sleep sensors may be used including EEG-based sensors,audio detection, motion detection, to determine various duration,status, depth, and suggestions. Hardware usage sensors may be used topassively collect data on usage of devices from sensors from mobilephones, portable audio devices, hands-free voice recognized playback andinternet driven cognitive computing devices, televisions, tablets,e-readers, hubs and providing a collection of information on charging,battery level, screen usage, interactions-touch, buttons, frequency,patterns, number of apps, app classification, app usage, call log, emailusage, SMS usage; and self-reported hobbies.

Measured economic data may include many sensing elements such as: newsrelated sensors, work-life balance sensors, finance related sensors, andhospital or care related sensors. News related sensors may include webcrawling and news media feeds for cognitive computing of news withreporting based on current location, surroundings or home, and friends'locations to define recipient recognizable personalized global tragicevents, global heightened security, global impact level and nationaltragic events, national heightened security, and national impact level;local tragic events, local heightened security, and local impact level.Work-life balance sensors or data may be collected through calendar,globally available calendars, and suggested activities planned inrelation to work-life balance, by measuring holiday-working and relatedstress; weekend-working and related stress; travel impact-cancellations,planned departure, delays, arrival times traffic-heavy traffic on route,crashes, police; and closures of an office or school. Finance relatedsensors or data may be collected through personal finance companies thatthe recipient provides access for assessing financial-gains, losses,stocks, investments, upcoming bills to pay, risks in due dates andrunning tight of funds for the month. The measured economic impact mayalso include hospital or care related sensors and data collected throughmedia, calendars, emails from hospitals or care providers including dataon hospitalization, births, deaths-importance, and impact level.

Measured behavioral data may include recipient and query-dependentactions, voice, facial and body recognition, including: user-computerreported actions for skipped queries—quantitative and qualitativereasoning on preferential alignment and emotive self-identification andreasoning; interactivity with the queries—patterns, heatmaps, usagetransactions, evaluation time and avoidances; abandoned queries—whethertimed out, ignored, or disabled; completed queries—quality of response(authenticity, valued—more like this, less like this), response patterns(e.g. same answer for similar questions), durations (answer latency);insights and lookups—transactional cues to educating response based onreported information, such as live tiles, links and references, andalignment predictors; and rating—crowdsourced, classifications (based onpersonality, or relevance) and prior personalized trending responses;activities with other systems, sensors, applications and functions ofthe query reporting equipment; tonality of the voice during audibleresponse—emotional states and attitudes (normal, sad, calm, bored,angry, panicked, joy, fear, stress, stability, neuroticism), personality(introverted, extroverted), deception, gender classification, age,physical size, prosodic characteristics (timbre, salience, pitch, rate,loudness, intensity, crackling); facial and body recognition—such asmicro-expressions (surprise, fear, disgust, anger, happiness, sadness,contempt, hate) using interrogation techniques such as the Reid method,and paralinguistics (facial expressions, gestures, body language, eyetracking).

Measured Relevancy Data may include both perceived and likelihood torespond meaningfully to queries and includes: classification andestimated likelihood; and contextual and estimated likelihood.

The present invention uses the data or data sets, as described herein,to create categorical based recipient profiles or to enhance one or morerecipient profiles. The system uses the data to identify attributes andcharacteristics of the data and how the data impacts the recipient'sbehavior (i.e. if and how they respond to queries). The data and themapping of the data to the recipient and query relevancy are primarilycategorical. The categories, as mentioned above, include, but are notlimited to: curriculum training; personalization data; personality typedata; self-categorization data; psychological data; measureddemographics; location data; ownership; environmental;physiological/genomic data; activity data; economic data; behavioraldata; and relevancy data.

As shown in FIG. 2, the System 20 utilizes significant amounts of datato adapt the query system. The Network 20 of the present inventionincludes the Adaptive Network Querying System 22 which is connected viainternet 24 or other communication methods to numerous devices and data.These devices and data segments include trainer devices and data 30,relational devices and data 40, recipient measurement devices data 50,external crowdsourced data 60, internal or system crowdsourced recipientdata 70, and crowdsourced service provider devices and data 80. TheAdaptive Network Querying System 22 is also accessible by one or moreadmins and users having roles and permissions as set forth in thesystems roles and permissions sub-system 26.

Within the trainer data 30, therein includes trainer questions, answersand images 32, a trainer mapping, relevancy mapping and personalitymappings element 34, and trainer devices 36, such as mobile devices, andtablets.

The relational data 40 includes genomics, genome mapping and genesequencing data 42, genealogy (genes, carrier, traits, risks) andancestry data 44, and personality mapping data 46. Personality mappingdata 46 may include data on personality types, such as whether arecipient is open to experiences, consciousness, extroversion,agreeableness, neuroticism, and other known types.

The recipient measurement section 50 includes health sensors 51,proximity sensors 52, environmental sensors 53, background data 54,personality data (type matching) 55, and recipient devices 56. Healthsensors 51 might include things like heart rate and weight monitoring ofdata and would provide physiological data measurements. The proximitysensors 52 might include things like location sensors and devices withlocation tracking data and would provide activity related datameasurements. The environmental sensor 53 would include sensorsmeasuring temperature, time, passively sensed, ancillary, or otherdirectly report data sources relevant to contextual cues and measuredenvironment data. The background and recipient historical data 54 mightinclude specific longitudinal history of the recipient, includinggenomics, and family history. The personality data 55 might includepersonality type matching information. Recipient devices 56 mightinclude the types of devices such as mobile, tablet, pc, the operatingsystems within those devices, and how they are used and the device as asensor.

The external crowdsourced section 60 might include real time data 62,medical data 64 and location data 66. The real time data 62 mightinclude data such as weather or trending news, and would provideeconomic related data measurements. The medical data 64 might includehistorical data, trending data in terms of population (upward anddownward risks, emerging, outbreaks, epidemic, and pandemic) anddemographic data. The location data 66 might include occurrence data,trending data, and interests.

In addition, the system may include internal or system crowdsourced data70 of recipients include relevancy mapping 72, personality mapping 74,and recipient devices 76.

Further, the crowdsourced service provider data 80 may include directcare 82, public safety 84, public health 86, and network health 88. Thedirect care 82 would include devices and data for direct care providessuch as information that is de-identified by a recipient's doctor orphysician's assistant. Public safety 84 would include devices and datasuch as police and fire or water and power through varying channels likepublic broadcast information. Public health 86 would include devices anddata such as local hospitals, ambulatory and CDC information. Thenetwork health 88 would include devices and data based on internetconnections, internet or provider health, uptime, and other similarnetwork and communication-based information.

The network 20 includes interaction amongst trainer section 30,relational section 40, recipient measurement section 50, externalcrowdsourced section 60, internal crowdsourced recipient section 70, andcrowdsourced service provider section 80 as used by the Adaptive NetworkQuerying System 22 to help formulate ideal queries or content based onrelevancy mapping 72, personality mapping 74 and other recipient -basedelements to provide system determined queries or content relevant andrelated to the recipient.

FIG. 3 provides a high-level network flow of data through the system100. It integrates permission roles of admins 140, 141, 142, 143, withone or more trainer roles 101, crowdsourced role information 120, andthe recipient role 199. The admins 140, 141, 142, 143 have the abilityto override any existing function of the system such as ignoringrelevancy for delivery or stopping new queries from being automaticallyaccepted into the machine learning environment. The admin reviewreporting mechanism looks at data modeling for saturation andperformance while distributing new tasks to trainers 101. Trainer 101could also be an admin. Trainer 101 injects and maps new content withnew classifications to drive a higher scoring for relevancy acrossvarying dimensions of recipients 199. These new classifications aremapped in a way that can be re-used when automatically collecting newtrending data points from crowd-sourced 120 information sources. Thecrowd-sourced data 120 derives new questions and content to improverelevancy through machine learning and adapting to a changing landscapeof health and world conditions. These new questions can be activelyinjected into the overall training program for new queries or they canbe sandboxed with acceptable rules set by Admins 140, 141, 142, 143 toensure a high degree of relevancy to the pool of questions intended forthe recipients 199. The recipient 199 can provide both a passivelysensed signal that helps correct the alignment and relevancy, while alsoproviding an active feedback loop on queries based on behaviors andpersonality.

Proceeding through the flow, the trainer 101 establishes base knowledgecurriculum 103 which is used to structure knowledge into training setsor lessons 105. These training programs are stored in step 107 and canultimately provide feedback for a scoring report 109 to an admin 143.The crowd-sourced data 120 can be utilized and in step 122 can measurepotential trending data. The trending data 122 is compared in step 125and can be adjusted in step 128 by an admin 142. Through the comparisonof trending data 125, the system then stores trending data 126 and thedata can be compared against personalized interests in step 162. Thestructured knowledge training sets or lessons 105 can also be comparedagainst trending relevancy in step 152.

The relevancy mapping 150 is also used in the comparison againsttrending relevancy in step 152. All recipient's personality mapping 160,which includes individual recipients 199, can be used in the comparisonstep 162. Based on the comparison of crowd trending data against allrecipient's personality mapping 160 in step 162 and the comparison oftrending data against all relevancy mapping 150, which includesindividual recipients 199, in step 152, the system can generate newqueries in step 153. Admin 141 would have the ability in step 146 tooverride any new queries.

In addition, the system 100 can measure the recipients 199 forpersonalization in step 172. The personalization is utilized in acomparison step 174 against stored personalization information 176. Anadmin 142 can also adjust, in step 178, the personalization comparisonparameters used in the comparison 174. The personalization is stored instep 176 and can be used in conjunction with the comparison step 164which uses an individual recipients' personality map pulled from allrecipient's personality mapping 160 against recipient-basedpersonalization from steps 172, 174 and 176. The comparison in 164scores personality against the personality algorithm including thealgorithm data 165. The individual recipient's relevancy map pulled fromall recipient's relevancy mapping 150 is then also compared, in step154, against the score personality from step 164 in determining a scorerelevancy of the knowledge set. The score personality from 164 and thescore relevancy from step 154 are then used to score training programsin step 111 for effectiveness across personality and relevancycategories. This score training comparison in step 111 also utilizes therelevancy mapping 150. The score training comparison in step 111 canalso have various overrides from step 145 which might be implemented byan admin 140.

Ultimately, the personality mapping 160, the relevancy mapping 150, andthe score training program 107 compared in step 111 are fed to theAdaptive Network Queries 170 which displays queries to the recipient andreceives responses. Such responses can be fed back into step 172 formeasuring the recipients for personalization. Through use of the system100, the training programs 107 and mappings 150, 160 can generate queryprograms which are effective for the specific recipient 199 based on therecipient's personality and relevancy to the questions.

The information flow may best be described using a set of queries goingfrom end to end through the system. By way of example, a query set maybe defined as a question, a set of responses and insights that arepresented after the recipient responds to the question. The insightsconsist of text, graphics, live feeds and data visualization contentcomponents. A system administrator, or a trainer, establishes groundtruth by programmatically loading the individual components of the queryset including the recipient or user interface templates into the systemvia a content publishing system such as a web-based, command line ordedicated client application. The templates include parameters such asthe question type (multiple choice, etc.), maximum number of responseoptions, max text length per question and response, max image size, datavisualization type displayed after the response is indicated,comparative definitions of the recipient response with responses fromthe population or sub-population for added insight to the recipient, andmax text length for a text-based insight displayed after the response isindicated. The properties of the templates also determine the recipientor user interface details that govern the format of the queries, andspecific content such as—font details, padding, positioning, text andthe image, etc.

Through the system, the admin/trainer uploads many (hundreds orthousands) of question sets, via pre-formatted files (such as delimitedformats like CSV) in a batch upload or other applications. The uploadedfile can help identify the template number to assist the system inmatching each question set to a preferred template.

The admin/trainer is able to execute each query set on the admininterface and is able to modify the content (text and images) to drivescoring categories from the ground truth. The admin then publishes thequery set or group of query sets. The query sets can initiate a datatransfer of the new query set to the end recipient's client. The systemutilizes algorithms to calculate relevancy and personality scores forthe different query sets. The relevancy scores are calculated on theserver and are periodically delivered to the client where they can bestored locally along with the query set parameters and content. Theclient and server interfaces collaborate and use the relevancy scoresand personality scores to determine the sequence of the query sets tothe recipient and whether to hide any particular query set. When the endrecipient interacts with the query set, via the recipient interface oruser interface, the system records the recipient's behaviors among othermeasured data and associated metadata and sends the recorded data backto the server. Although measured data can be sent at any time, it isimportant to collect the contextual data at the time of the queryresponse. The admin user can view the calculated weightings for aparticular query set and can override the calculated score in order tomanually drive sequence priority or show/hide specific queries.

FIG. 4 provides that the process flow 200 detailing the trainer-baseddata installation through analysis and integration of relevancy mapping150 and personality mapping 160. The trainer 101 records training datainto a set of structured databases 205. The trainer then establishesground truth by mapping these data sources and the relationships betweenquery sets for questions and answer sources in step 207. Therelationships are then mapped and stored in a database 210. In addition,the trainer sets up various training databases 220 and those databasesmay include a questions database 221, question classifier database 222,question image database 223, question scoring database 224, pre-definedanswer database 225, an answer classifier database 226, an answer imagedatabase 227, and an answer scoring database 228. These trainingdatabases 220 are in communication with the mapping data sources andrelationship data 207 and are also tied to the trainer executing eachquestion and answer to confirm scoring categories in step 212. Based onthese scoring categories 212, rankings are created in step 214,including creating tags which provide an indication of the adaptivenetwork strength for a diverse set of trending, relevancy andpersonality. These rankings integrate the relevancy mapping 150 of thequeries as well as the personality mapping 160 of the recipient. Thequeries need not be questions and could be content in non-query format.

Once the information is mapped and ground truth establish, it isexecuted to ensure that there is sufficient coverage for the confidencelevels across varying relevancy mapping 150 and personality mapping 160.These confidence levels translate to scored rankings which in turn canbe used to further develop the system through crowd-sourced trending. Ifa certain demographic, age, location, gender identification, or otherattribute is under-covered, meaning coverage does not meet an expectedquantitative limit, then it can be prioritized for additional automatedtraining through external linkages. Further, the system can calculate arelevance score for each question set that is associated with aparticular recipient and a relevance score that is independent of therecipient. The Recipient Specific Relevance Score (“RSRS”) considers thespecific recipient's context, such as inferred levels of engagement, thehistory of the particular user's interactions with the query sets. TheRSRS may also classify recipients into groups of similar or relatedrecipients. The Recipient Independent Relevance Score (“RIRS”) accountsfor what topics are trending nationwide and calculates a score based onhow closely the topic of the question set matches the trending topic.The RIRS further accounts for the inferred level of engagement from thepopulation of recipients as a whole (i.e. whether people in general areinteracting with the questions set). If the topic is trending and therecipients are interacting with the question set, then the RIRS will behigh and if the topic is trending but recipients are not interactingwith the question set then the RIRS will be lower. The RIRS and RSRS areused to calculate the total relevance score (“TRS”) which directlydrives the end recipient experience with a particular query set.

The relevance scores are computed by analyzing the recipient's behaviorand other measured data, recipient responses, question properties,trending and other crowdsourced data, and past relevance. The recipientbehavior analysis includes behavior measured data such as how therecipient interacted with the question, was it abandoned or completed,or did the user click on the insight link for more information. Therecipient response data is used to analyze the existing recipientprofile data, and other longitudinal and collected measured data of aparticular recipient. The question properties may refer to a specifictemplate or UI form, question type, contextual tags, length ofquestions, number or response options, and the insight visualizationtype. Trending linkages involves an analysis of the linkage between thequestion topic area and the topics that are currently trending, and thetrending is assessed on a global, national regional and local scale.

Using the relevance score, the system or network makes automaticadaptions for the recipient. These adaptions can change the experiencefor specific recipient s or groups of recipient s or all end recipients, change the sequence/priority of questions, remove a question or setof questions from circulation, hide a question or set of questions froma subset of recipient s, change the visualization type in the insightfor a question template, and change the reading level. The relevancescore will be stored in the analytic database that includes the inputs,outputs, automated system actions, manual actions and algorithmversions. The database will further store calculated relevance scores ofeach question, calculated relevance scores of strengths of trendinglinkages, and offer exportable reports.

The goal of the systematic questions is to allow the network to inferrelations between varying topics and to suggest further queries based onresponses from one question to the next. Queries can cover many topics.For example, they may cover aspects related to wellness, health andquality of life. These health queries may go to the fundamentalfoundation of overall wellness of the recipient narrowing the focus onthe health of recipients' mind and body to assess wellness. Overallhealth of the mind and body are determined with queries dealing withbasic survival needs, mental health and sleep revitalization. MentalHealth, sleep revitalization and basic survival needs are assessed withqueries based on the recipient's cognition, exercise, diet andnutrition. The overall health of these topics are assessed using querieswhich assess the recipient's neuro state, cardio respiratory andmetabolism. These categories can be assessed based off queries relatedto chronic diseases and risky behavior such as working too much,sleeping too much, eating too much, etc. Which can be assessed based onquestions of about recipient's health care, which can be assessed usinggeneral quality of life queries.

FIG. 5 presents an additional flow 300 with the recipient 199, throughthe client device, detects a new query 302 and depending on theavailability of the query a scoring is triggered on the informationavailable and ultimately delivered. The Adaptive Query Network 370 thencompares personality data in step 361 using the personality mapping 160of the recipient 199. In addition, relevancy mapping 150 is alsoutilized in a relevancy data comparison in step 351. Ultimately, thepersonality data comparison 361 and the relevancy data comparison 351are used to score the data in step 362. The personality data comparison361 and the relevancy data comparison 351 and the score data 362 are allutilized to determine the delivery in step 364, the actual delivery ofqueries in step 366 to the recipient 398. Feedback is provided in step368 which is then used to update the relevancy based on personality instep 369. This updated relevancy is then used to update and/or enhancethe relevancy mapping 150. In addition, the feedback along withadditional data including environmental data 310, physiological data312, profile data 314, and activity data 316 are used to comparetrending data in step 324. The trending data comparison 324 may interactwith a sampling rate and scheduler 320 which determines how often sampledata from the external sources change in step 322. The comparison oftending data in step 324 is then stored in step 326 which is stored inone or more sample databases 328. The system 300 also looks within thetrending data to detect new changes in step 330. The data with changesis then updated and tagged in step 332 to identify more relevanttrending data. In addition, the new changes identified in step 330 arethen also used and compared against the personality data in step 335.The personality data comparison 335 can be used to update or supplementthe personality mapping 160 as well as update specific tagging andtrending data specific to the personality data in step 337. The updatescan be stored in one or more databases 328. Through this scenario, arecipient 199 can have relevant queries based on their personalitymapping 160 and relevancy mapping 150 taking into account the variousdata, 310, 312, 314, 316 which factors trending data as well as therecipients specific profile in relation to both the queries and trendingdata at the current time of the query.

As seen in FIG. 6, the present invention also integrates the use ofcrowd-sourced data 120 which can be received into the system 400 throughone or more external sources. The crowd-sourced data 120 and informationcan utilize existing training to generate new queries and responses. Thecrowd-sourced data 120 interacts with a scheduler 421 in which thesystem 400 can retrieve training data 424 which includes questionclassifiers 422 and question scoring data 423. The system 400 thencreates, step 425, search lists based on tags, topics and scoringpreferences in step 425. In step 426, sources are scanned for newinformation. Such new information would include data from sourcedatabases 428. The system then compares the trending data in step 429with global trend data 430, global data sources 431, and crowd-sourceddata 432 which are compared in step 429. The comparison 429 then storesthe trending data 435 including storing it in the trend database 440.The crowd-sourced data compared against global trending data is thenanalyzed to detect new trending data in step 437. The system 400 canthen update and tag this trending data in step 439 and save it in anappropriate database 440. Ultimately, the detection of new trending data437 is then compared against relevancy data 451 and personality data461. The relevancy data comparison 451 utilizes the relevancy mapping150 while the personality data comparison 461 uses the personalitymapping 160. Through the relevancy data comparison 451 and personalitydata comparison 461 the system then can map topics to questions andclassifications or classifiers in step 462 leading to the systemidentifying an appropriate format topic based upon relevant mappingincluding suggestions on relevant images, relevant tags, and relevantclassifiers in step 466. The system 400 then stores the updated topic,question and answer mapping to the training database in step 468 whichis then also used to update the relationship mapping database 210. It isimportant to note that the relevancy data comparison 451 and personalitydata comparison 461 also lead to updating the trending database and thetraining database 464.

The present invention also uses machine learning in addition to crowdsourced data to generate new queries and responses. The Adaptive NetworkQuery System has a machine learning component that uses artificial,computer generated, users to categorize and assess new queries. Afterthe system processes the new queries through the artificial recipientsand how the artificial recipients have responded to the queries, thesystem will categorize, tag, and map (relevancy and personality) theresponses. As the new queries are released, the artificially cataloguedresponses will be further refined as the recipients interact with thequeries. Further, as actual recipients expand. the total profilesavailable will also expand the artificial profiles used by the machinelearning function.

However, the system structure need not be traditional server-sidearchitecture. The system could employ system-less or unbounded design.This unbounded design means the system could employ virtualization,containerization, or other solutions to create independence fromspecific architecture, software, cloud, or other features.

As seen in FIG. 7, the Adaptive Network Query System (“ANQS”) 500includes the ANQS client component 530 and the ANQS server 550 whichform part of the network 522. The client 530 may be connected to theserver 550 via a private network 510 or a public network 512. The client530 includes the network manager 531, the recipient or user interface533, the bandwidth manager 534, the inter-process communication (IPC)manager 535, the storage manager 536, and the battery manager 538. Theserver side 550 includes a network manager 551, a training manager 553,the machine learning component 554, the mapping engines 555, the storagemanager 556, and the trending engines component 557.

The client 530 also includes the local system or platform 560 whichincludes one or more processing components 562 and transactionalcommunication component 561 such as an Operating Systems (OS) APIfunctionality as a given example method for transactional communicationbetween the ANQS Client Component 530 and the local system 560. Thelocal platform 560 of the client 550 includes all appropriate processingelements to process and manage the client components 531, 533, 534, 535,536, 538. The server side 550 includes the remote system or platform 570which includes one or more processing components 572 and a transactionalcommunication component 571 such as an Operating Systems (OS) APIfunctionality as a given example method for transactional communicationbetween the ANQS Server Component 550 and the remote system or systems570. The remote system 570 also has additional elements to process theserver-side components 551, 553, 554, 555, 556, 557.

The client component 530 receives updates from server component 550. Theclient network manager 531 has configuration controls that the localinter-process (“IPC”) manager 535 can utilize to improve bandwidthusage, battery usage and storage usage through their respective managers534, 536, 538. The IPC manager 535 coordinates activities, bandwidth,storage, and battery on a local system 530 in conjunction with theremote server system 550. The IPC manager 535 reduces the informationbetween the server 550 and client 535 and the customization to theindividual personalization and relevancy.

A set of configuration controls that are retrieved from the server 550and are managed within the client 530 within its profile manager definesa client profile which includes many areas of managed user data forclassifying appearance, perception of relevancy, and personality.Included in this profile, is a client hardware represented model whichthe IPC utilizes to improve usefulness of the hardware to the recipientwithout overloading and stressing limitations for reduced performanceand brand satisfaction. Some example client hardware profiles include:optimized for low power, optimized for metered connections, optimizedfor small storages, balanced optimizations options, and highperformance. A high-performance profile may store less and require morepower and bandwidth than other profiles, with the gain that the contentdelivered is fast and fresh. Whereas, a balanced option may becustomized to the hardware and can vary from mobile hardware models toperformance IoT gateways to low power wearable gateways. In contrast, asystem that is always plugged in may not include a profile for battery.A system that is a flagship mobile with very large storage capacity maynot have storage concerns. A system that is a wearable gateway may havea high degree of concern on battery usage. Further, characterization ofnetwork and storage access may suggest in some cases that large contentprocessing from a local storage may be more battery intensive thatnetwork processing and may allow for limited storage while focusing onnetwork protocol proficiency such as tradeoffs in Wi-Fi versus Cellular,versus Bluetooth Low Energy. Further, any consideration on theconfiguration controls changing may be based on the recipient and theirPersonality Mapping/Relevancy Mapping (not the type of device); time ofday; historical recipient interaction (low power in evenings; highperformance in mornings) and other factors and attributes.

As previously discussed, the Personality Mapping and Relevancy Mappingwill impact both the Profile Manager and the Recipient or User InterfaceManager. The inferred result of the personality mapping may hide,arrange, or replace UI components. These UI components may be storedlocally but would require profile changes to adapt to new networkrequirements if the UI builder requires a new set of information, orlive feeds based on the ability to complement their needs.

Live feeds are a mechanism for providing dynamic content to helprecipient engagement and responsiveness to varying lines of queries. Insome cases, live feeds can provide an educational tool to the query forthe recipient to increase their skillset in response and responsiveness.Live feeds can also be relevant to the user to describe current localevents such as news feeds, weather, public health information and safetyinformation. In addition, as part of insights, live feeds can provideuseful go to information that the recipient can utilize for scoring andfuture queries.

Further, FIG. 7 shows the information flow of server 550 and client 530communication related to the ANQS system 500 with the client 530receiving communication by the server-side network manager 551 to theclient-side network manager 531. The client 530 receives a configurationbased on its overall hardware, a dedicated IoT gateway versus a mobilephone will have customized configurations that would be received duringan initial communication with the server. These profiles can be locallycustomized on the hardware through adaptive needs of the system orrecipient preferences, needs and other situations like system overridesfrom an administrator.

These configurations define controls that the IPC Manager 535 uses tobalance the usage of content storage, and requests to the networkmanager 531 for more information on an as needed basis versus alwaysneeded basis. The IPC Manager 535 receives updates from the bandwidthmanager 534 to produce a larger number of updates if the system 500 isusing a high bandwidth non-metered connection. The IPC Manager 535 andBandwidth Manager 534 and also reduce the update requests if theconnection becomes metered or the bandwidth reduces which can causedownstream lag to the recipient from a recipient or user interfaceperspective. A larger number of API requests and content requests over aslower connection will also consume more power due to processing needsand likewise battery usage. Thus, the battery manager 538 is used toreport the battery usage as an additional measure to the IPC Manager 535to help with balancing the needs of the system 500 with theconfiguration of ANQS client 530.

As seen in FIG. 8, the client side of the present invention includesadditional elements from those shown in FIG. 7. The client 600 includesthe network manager 531, the IPC manager 535, the storage manager 536,the battery manager 538, and the bandwidth manager 534. In addition, theclient 600 includes the network manager 531 interacting with one or moreconfiguration profiles 641. These configuration profiles 641 helpdetermine configurations of both the client device as well asconfiguration of the recipient. The configuration profile 641 is used bythe IPC manager 535 to identify and set up various controls related tothe device 530 and is used by the network manager 531. In addition, theIPC manager 535 interacts with an application manager 640 to identifyand publish the appropriate recipient or user interface 642.

The bandwidth manager interacts with and passively senses data about thecellular network 602, the WIFI network 604, and Bluetooth communication606. The battery manager 538 interacts with the battery 603 and anypassive sensing of the status of whether the client 530 is using thebattery 603 or is plugged in 605. Ultimately, the client 530 through theIPC manager 535 can identify and determine, based on the configurationprofile 641 and the application manger 640, an optimal recipient or userinterface 642 taking into account the bandwidth manager 534determination of bandwidth availability and the battery manager 538sensing and determining the optimal power consumption. Though use of theconfiguration profile 641, the IPC manager 535 can determine if queriespresented to the recipient or user interface 642 presented to therecipient need to be modified based on the bandwidth, battery, andconfiguration profile.

FIG. 9 depicts an additional element of the present invention as furtherdetailed in relation to FIG. 8 above. As seen in FIG. 9, the client side630 includes the IPC manager 535, network manager 531, storage manager536, battery manager 538, and bandwidth manager 534. However, inaddition to the various manager components, the system also includes aprofile manager 645, a profile manager builder 649, a recipient or userinterface manager 660, a recipient or user interface builder 664, and arecipient or user interface controller or adapter 662. Through thisenhanced system, the IPC manager 535 works with the configurationprofile 641 to identify various aspects of the client device 630 and theprofile of the recipient based on various aspects of interactivity ofthe recipient with the device and external data.

The system can use multiple configuration profiles 646, 647, 648 whichare available to the profile manager 645 for use in application based onthe profile manager 645 determination of the configuration profile 646,647, 648 most likely to represent the real time personality profile forthe recipient. In the event the configuration profiles 646, 647, 648 arenot an appropriate profile for the determined profile of the recipientfor the time that the query needs to be presented, the profile managerbuilder 649 can create a profile based on the known elements of arecipient profile and filling in any determined gaps to build a newconfiguration profile that would also then be stored and managed by theprofile manager 645. Ultimately, the selected configuration profile 646,647, 648 or a new profile built by the profile manager builder 649 willbe used to determine a final configuration profile 641 which is thenused by the IPC manager535 to determine or alter the queries coming infrom the network manager 531.

In addition, the system 650 includes components which help the client630 determine an appropriate recipient or user interface from theexisting recipient or user interface forms or templates from the UIForms database 661 or to adapt (step 662) or build (step 664) a newrecipient or user interface more appropriate to the real time profile ofthe recipient. The recipient or user interface manager 660 determines ifany of the UI forms 661 are appropriate based on the profile determinedby the profile manager 645. In the event the UI forms 661 are deemedinsufficient, the recipient or user interface manager 660 determines ifthe recipient or user interface can be adapted or controlled to create arecipient or user interface appropriate for the configuration profile641 or if a new recipient or user interface is required to be built bythe recipient or user interface builder 664. Ultimately, a selected,adapted, or built recipient or user interface is presented to theapplication manager 640 for display on the client 630.

The recipient or user interface templates or forms used by the systemfor presenting queries to recipients are also based on the rules and thedecision mapping engine of the system. The templates, rules, and mappingengine are downloaded to the client or device as needed during initiallogin and other synchronization needs during client usage. The contentof these forms can also be stored locally in the local client withrelevancy, personalization mapping and trending signaling occurring fromthe remote server with less redundancy in the sharing of the content,where the client can update when the server signals updates areavailable.

Requests for UI templates or forms may come from the server based on oneor all of the following: Intent to send (rules or admin requested);trending/crowdsourced data, and recipient data (relevancy andpersonality). When the client, receives a notification from the serverof an intent to send a query, the client must determine whether it hasthe necessary information or whether it requires more from the server.The server may provide suggestions in the notification of the profilethe client should use to reduce the over the air communication time.However, the client may need a different UI form if the profilesuggested is not appropriate, new or additional images are needed, ormay have updated its profile. Further still, the decision making on theclient may be limited based on client performance needs, storage space,networking—which may in part request more content or less when a requestcomes from the server. The system, including the server and client, haveappropriate rules for handling and resolving the best alternative basedon network limitations such as performance, bandwidth, and connectivity.

The system also makes use of a personality processing model whichdefines the recipient's personality to gain an understanding of whattypes of queries should be asked. Some individuals will respondnegatively to questions or lose trust in the system if not asked in anappropriate manner. This provides a layer that can directly influencethe relevancy scoring to ensure a higher degree of good qualityresponses for queries delivered or plan to be delivered. The enrollmentfor a specific personalized model could be based on varying psychologyand personality mapping techniques, including OCEAN and Myers Briggs.

Continuing with FIG. 9, the IPC manager 535 also manages the profilemanager 645 and the application manager 640 to control or limit some ofthe functionality of the profile manager 645 or recipient or userinterface manager 660 based upon the bandwidth manager 534, batterymanager 538 and storage manger 536. By way of example, if the batterymanager 538 determines that the client 630 is low on power and profilemanagement building through the profile manager builder 649 or recipientor user interface building through the recipient or user interfacebuilder 664, would be too process intensive, the IPC manager 535 mayinstruct the profile manager 645 to limit profile selection to a profilethat currently exists or may limit the recipient or user interfacemanager to select a UI Form 661 that already exists. Further, the IPCmanager 535 through the storage manager 536 may limit the storage of anew recipient or user interface or adapted interface or may instruct theStorage Manager 536 to delete or purge seldom used data (profiles, UIForms, and other date) in the event the database 537 is deemed to benearing its memory capacity. Further the bandwidth manager 534 can helpidentify various communication paths, the reliability of such paths andthe data transmission speed to determine if elements missing within anyprofile or recipient or user interface can be retrieved thereby allowingthe IPC manager 535 to control the final configuration profile, thefinal displayed recipient or user interface or UI form, and the querypresented to the recipient.

The interaction of the client 530 and server 550 with regards to theprofile manager 645 and recipient or user interface manager 660 aredescribed in conjunction with FIG. 10. As seen in FIG. 10, the client530 through the IPC manager 535 and the network manager 531 communicatewith the server-side network manager 551. The client 530 includes theIPC manager 535, the storage manager 536, the database or memory 537, aswell as, the profile manager 645, the profile manager builder 649, theapplication manager 640, the recipient or user interface manager 660, UIforms database 661, the recipient or user interface builder 664, and therecipient or user interface adapter or controller 662.

On the server side 550, the network manager 551 interacts with themachine learning component 705 and the numerous databases available andaccessible through the system. The databases include the relevancymapping database 150, the personality mapping database 160, therecipient database 709, the trends database 440, the UI forms database661, the profile database 662, the training database 220, and therelationship mapping database 210. The databases and machine learningcomponent 705 interact with the recipient manager 707 and the deliverymanager 709 to present appropriate queries back to the network manager551 for passing to the client 530. The server side 550 also interactswith the mapping engines 555, the trending engines 557 and the trainingmanager 553 to continue to map the recipient's profile, theconfigurations, and the queries in combination with the various dataavailable to the server 550 to help refine the knowledge base of thesystem, and the recipient profile learning on the server side 550.Through interaction of the knowledge database and machine learning 705on the server side 550 and the logic and capabilities on the client side530, the system is able to provide anticipated queries and recipient oruser interface instructions to the client 530. The client 530 is able tomake customizations in real time based upon real time profile managementof the recipient and real time recipient or user interface management onthe device.

FIG. 11 provides the flow 800 of the interaction from the server 801 tothe client as it relates to the messaging provided to the client. Theflow 800 is initiated by the server 801 when the system determines itneeds to send a query 802 to a recipient. The system 800 reviews thecontents of the query 803 and then processes the content through one ormore filters 805 which includes a review of the recipient profile 806based on the systems determined profile for the recipient at such time.When the system 800 has processed the query content, filtered andassessed it against the profile 806, it generates a message 808 which isthen sent to the client 810.

The client, in step 815, receives, parses, and analyzes the message intothe various components related to the server's assessment of theappropriate recipient profile and the appropriate UI. The client in step815 also identifies any gaps within the profile data, query data, andrecipient or user interface data and can respond back to the serveralong path 816 to fill any gaps. The analyzed message is then reviewedto determine the profile against the determination of the recipient'sreal time optimal profile as determined by the client device. Theprofile sent by the server may be a partial transmission based on thelast known transmission. This partial transmission may be merged in step821 with the client if error checking determines merge to be accurateand valid. If any errors are detected and repairs cannot be made, thenthe full profile file would be requested for transmission from theserver. To the extent the client message includes a profile which agreeswith the client-side determination then the client picks the profile instep 820 from the host of profiles available on the client. In the eventthe client message contains a profile which is not available on theclient, the client then builds a profile in step 825, stores the profilein 827 and passes the profile along to the recipient or user interfaceportion of the flow. The determined profile, either built or selected,is then utilized by the system to determine an appropriate recipient oruser interface along with the interface suggestions contained within theoriginal message to the client. The system analyzes the suggestedrecipient or user interface from the message as well as makes anyadjustments based on the determined profile and determines if arecipient or user interface exists within the system or needs to bebuilt. If the client system determines the recipient or user interfacealready exists, the client will pick the appropriate UI in step 830. Ifthe client determines the recipient or user interface does not existwithin the UI forms or templates available on the client, then theclient application will build a new UI in step 835, store the UI in step837 and ultimately display the UI in step 840. The selected or built UIbased on the communications from the server as well as the analysisdetermined related to the recipients then current profile. Ultimately,this information is synced in step 842 back the server 801 so that theserver side can continue to use machine learning to further understandthe recipient and to alter the database for both training andknowledge-based purposes.

In a preferred embodiment, the file transmitted in the message, whetherpartial or full, is structured as both filename and file content, ornotation of changed content, with potentially multiple streams ofcompressed and uncompressed data. The filename provides an initial cueas to the existing profile relationship to the recipient. It containsflags represented as conventional letters, numbers and positions withinthe filename for network, battery, storage, timestamp, last transmissionidentifier, checksum (hash, CRC, SHA, MD5 or other method) and asimplified template guide based on personality, relevance and previousmeasured source data. The initial elements of the file within themessage provide a quick check in comparing client and server copies andany changes therein. If there is a mismatch, then the contents in anobject-notation (XML, JSON) are compared for deeper checks and merging.Each field within the file has a timestamp and related information, ifthe client profile file or information is out of sync with the serverprofile file or information, then the client will merge latest changeswith the server. Only the file differences need be shared. The onlycondition where the file is replaced, is if the file is corrupt, thenthe client would replace the entire file in that case or the serverwould if such a case constituted the change. Within the file there is abreakdown of individualized content for varying queries classifiers. Thepresent invention provides the ability to have a unique approach todifferent queries and not a single approach to one type of template orrotating template. Rather, the present invention provides a uniquetemplate which is provided or utilized based on the depth of theclassification of the training DBs, the personality and the relevancymappings.

The resulting output from the activity of the Adaptive Network QuerySystem helps to transform queries into more appropriate messaginginclined to engage a recipient based on the recipients then currentpersonality or state of mind.

FIG. 12 depicts various queries in varying recipient or user interfacesand presents various examples resulting from the system of the presentinvention. A sample query template 901 presents a basic set of questions902 which may include an image 903 to a recipient. However, the query901 provides little personalization to the user let alone takes intoaccount the recipient's then current state of mind. However, through thesystem, the recipient interface form or template can have varyingelements which can be modified, altered or added in addition tomodification of the query content and format of the content to presentthe recipient a far more tailored interface based on the recipient'slearned and real time determined profile.

By way of an example, if the system determines that the current state ofmind of the recipient, that is undergoing cancer treatment recovery,suggests a general state of depression, the system may determine andthen configure the query in multiple ways. First, the recipient state ofwellness would be known through measured data collection sources, andthe condition of depression may be inferred by the recipient's semanticlocation of home, geo-location based on relative IP address or GPS,longitudinal array of past 4 days, weather patterns, and lack ofinteraction with device or significant interaction (i.e. limited callsor texts). On day 5 (the day a query is to be presented), if therecipient has not moved and the system determines additional scenarioswhich can compound, or influence (such as gloomy weather, lack ofactivity, poor sleep, poor diet, weight gain, water loss, increasedblood pressure, increased alcohol, increased television or internetusage), then the system or device may determine the recipient issuffering depression or depression like activities. Thus, based onpersonality and mapping of what works best for different individuals,the recipient may see one of the query sets. The system may determinerather than asking “How are you feeling following your cancertreatment?” or even alternately “Are you depressed?” the system restatesthe query based on the scenario as “Time to get out!” with detaildriven, and possibly live data and following question (and perhapsresponse) the system suggests the recipient to take action. The systemmay determine a single response is most appropriate to reduce time spenton the question without collecting too much from the recipient.Alternatively, the system may determine it is appropriate based on therecipient profile to provide a brief description, moderately logical,but more communication driven. Instead of asking “Are you depressed?”the system restates the query based on the scenario “What a nice day!”and following questions are purposed in a way that suggests therecipient to get involved and be active. Further, the system may notprovide any description but prompts an action. Instead of asking “Areyou depressed?” the system assumes some social interactions are requiredand restates as “Time for a hug!”. The action they are to complete maybe one action or one of several actions from a list and report which onethey are most inclined to perform.

As seen in FIG. 12, these queries and prompts are integrated into thevarious sections or elements of the template. The system 900 helpstransform or replace a standard query template 901 into personalityprofile focused templates 910, 920, 930 based on the recipients'personality type (Personality A, B, C for example) as reflected in therecipient profile stored in the system and client. For example, astandard query template 901 may have an upper element 902 and a bottomgraphical element 903 for presenting queries. In contrast, apersonality-based template 910, 920, 930 may present queries with anupper window 917, lower window 915 and graphical elements 916, 918.These windows 915, 917 and elements 916, 918 can be presented to therecipient in ways that provide detailed or graphical information in areadily decipherable manner. The graphics 916, 918 and the text may beselected, retrieved, or built based on the recipients then currentprofile.

The system of the present invention contains an Interpreter 905, whichupon receiving a query can reinterpret standard templates using variouscriteria. The interpreter 905 processes the query and determines thepersonality type, profile of the recipient and then determines: thetemplate to use; the graphical elements to use; the query format; thenfinalizes the combined content of the query, and determines theplacement or location of the query content (images and data) to displayin the selected windows of the selected template.

In the event the profile indicates the recipient has previously shownthat they prefer graphical elements for longitudinal data 918 ormultiple days versus specific information on the then current real timestatus 916, the system can present a host of information and images asseen in interface 910 or limited live imagery and data as seen ininterface 920 and even more limited as seen in interface 930. Inaddition, the format of the question can be presented in multipleformats such as attempting to prompt the recipient where they are goingas opposed to specific things that they may be planning for the day asseen in 925 or based on the profile determines the recipient needsinteraction and prompts the recipient for interaction rather thanspecifically asking a query to get the recipient to engage the systemprior to asking things about what the recipient's going to do or wherethe recipient's going to go as seen in section 935.

Ultimately the system can use the configuration profile of the recipientand the UI forms available or the UI builder to assemble various queriesas presented in windows 915, 925, 935 within the various templates 910,920, 930 and to present numerous graphics 916, 918, 926, 936 in amultitude of forms and formats to best engage the recipient based on therecipient's real time profile. As previously described, the queriescould be content, not in the form of a question, and the system couldreword or reconfigure the content (change tense, tone, argument) anddetermine location of the content within the templates and interface.

Insights are presented after the recipient responds to the query. Theinsights consist of text, graphic and data visualization contentcomponents. The end recipient learns how their answer compares with theanswers of other people. Which group of other recipient s in the systemthat are included in the comparison, is governed by the parameters ofthe template. For example, the admin can configure the template toinclude a comparison group that includes only people with diabetes orother criteria. The Insight template also includes a short textdescription of a fact related to the question that helps the endrecipient learn something about the topic area. Variations on theInsight template includes the responses of the specific recipient arehighlighted in the visualization. In this template the “quick insight”also includes a hyperlink to a web page that includes content about thetopic area. Another variation is an Insight template that includes afilter where the end recipient can select from a set of options thatfurther filter the comparison criteria to a subset.

FIG. 13 provides a comparison 950 of the messaging of legacy systems 951against the messaging of the current system 960 and an alternativeembodiment of the present invention 971. In a known server to clientmessaging protocol 951, a notification 953 is sent from the server sideto the client. The client then in 954 sends a message back authorizingthe communication and requesting more information such information maymean it's the type of form to use. The server side then sends theadditional information in step 955 back to the client in a form maybe ina form template. This process continues back and forth in what is knownas an overhead web driven based messaging format 952. Ultimately throughthe back and forth between the client and server, a template can betransmitted, the title and queries, question types and questions and anyimages can be transmitted back and forth somewhat in either a multitudeof messages or packet of messaging finally terminating in step 959 withthe client notifying it has all of the authorization and a full responseback to the server. The problem with the current messaging format 951,is that the system requires significant communications back and forthbetween the client and server resulting in increased bandwidth andpotential issues in communication and connectivity.

The present invention provides a messaging system 960 which allows theserver side to notify the client and include the new message 962 whichincludes the sever side's information on the query and the server sideidentified profile and recommended UI template. Because the client sidehas their own ability to now modify the profile and/or modify the UItemplate, the client can send a notification of the authorization andresponse 963 back to the server indicating the client has everything itneeds. Ultimately, then the client will make determinations on does ithave an appropriate profile, can it select the appropriate profile, doesit need to build a new profile, does it have the appropriate UI form,does it need to build a UI form, and can it ultimately assemble thequeries within a selected template with selected images, and selected oradapted query format to present the recipient with the query in a clientside optimized format.

Still further, the system has the ability to make additionalcustomizations through a secondary embodiment of a communicationcomparison 971 where the server sends a notification and message 972 tothe client. The client then would send an authorization or request formore information 973 based upon either certain custom elements that areneeded or gaps in information or gaps within the server message incommunication step 973. The server in step 974 can send the additionalcustom information back to the client for the client to build andidentify the final UI based on the final configuration profiledetermined by the client and send an authorization and response back tothe server in communication step 975. Ultimately, the communicationstructure 960, 971 significantly reduces the significant number ofclient-to-server and server-to-client communications for repeatedrequests of additional information to build a template and/or structurea query in an appropriate format for the real time personalitydetermination of the system.

In an alternative embodiment, the server may include a profile manager,a profile builder, a recipient or user interface manager, a recipient oruser interface builder, and a recipient or user interface controller oradapter. The server may ping the client device to obtain the client'sdetermination of best current configuration profile or data to determinea best current configuration profile. The server may then select,through the profile manager, a configuration profile to use. In theevent the system determines the optimal current profile does not existin the system memory, the profile builder can create or assemble areal-time profile for use.

The server profile manager then communicates the real time profile tothe server-side recipient or user interface manager which determine anappropriate recipient or user interface. The recipient or user interfacemay come from an existing user interface form stored in memory. In theevent the server recipient or user interface manager determines thestored UI forms are deemed insufficient, the server-side recipient oruser interface manager determines if a stored recipient or userinterface can be adapted or controlled to create a recipient appropriateUI form or if a new UI form is needed. If a new UI is needed, the userinterface manager communicates with the recipient or user interfacebuilder to build a new UI form or template based on the real-timerecipient profile. The server than determines any additionalmodifications to the queries, wording, and graphics and transmits theinformation to the client. The information may include the profile, UIform, and query or may be instructions for the client to build amatching profile, UI form, for displaying the query and any relatedimages on the display of the client device.

The systems and methods of the invention in described embodiments may beimplemented as a system, method, apparatus or article of manufactureusing programming and/or engineering techniques related to software,firmware, hardware, or any combination thereof. The described operationsmay be implemented as code maintained in a “computer readable medium”,where a processor may read and execute the code from the computerreadable medium. A computer readable medium may comprise media such asmagnetic storage medium (e.g., hard disk drives, floppy disks, tape,etc.), optical storage (CD-ROMs, DVDs, optical disks, etc.), volatileand non-volatile memory devices (e.g., EEPROMs, ROMs, PROMs, RAMs,DRAMs, SRAMs, Flash Memory, firmware, programmable logic, etc.), etc.The code implementing the described operations may be furtherimplemented in hardware logic (e.g., an integrated circuit chip,Programmable Gate Array (PGA), Application Specific Integrated Circuit(ASIC), etc.). Still further, the code implementing the describedoperations may be implemented in “transmission signals”, wheretransmission signals may propagate through space or through atransmission media, such as an optical fiber, copper wire, etc. Thetransmission signals in which the code or logic is encoded may furthercomprise a wireless signal, satellite transmission, radio waves,infrared signals, Bluetooth, etc. The transmission signals in which thecode or logic is encoded is capable of being transmitted by atransmitting station and received by a receiving station, where the codeor logic encoded in the transmission signal may be decoded and stored inhardware or a computer readable medium at the receiving and transmittingstations or devices. An “article of manufacture” comprises computerreadable medium, hardware logic, and/or transmission signals in whichcode may be implemented. A device in which the code implementing thedescribed embodiments of operations is encoded may comprise a computerreadable medium or hardware logic. Of course, those skilled in the artwill recognize that many modifications may be made to this configurationwithout departing from the scope of the present invention, and that thearticle of manufacture may comprise suitable information bearing mediumknown in the art.

In an embodiment of the invention, the systems and methods use networks,wherein, the term, ‘networks’ means a system allowing interactionbetween two or more electronic devices, and includes any form ofinter/intra enterprise environment such as the world wide web, LocalArea Network (LAN), Wide Area Network (WAN), Storage Area Network (SAN)or any form of Intranet.

In an embodiment of the invention, the systems and methods can bepracticed using any electronic device. An electronic device for thepurpose of this invention is selected from any device capable ofprocessing or representing data to a recipient and user and providingaccess to a network or any system similar to the internet, wherein theelectronic device may be selected from but not limited to, personalcomputers, mobile phones, laptops, palmtops, tablets, portable mediaplayers and personal digital assistants.

As noted above, the processing machine used to implement the inventionmay be a suitable computer or other processing machine. The processingmachine may also utilize (or be in the form of) any of a wide variety ofother technologies including a special purpose computer, a computersystem including a microcomputer, mini-computer or mainframe forexample, a programmed microprocessor, a micro-controller, a peripheralintegrated circuit element, a CSIC (Consumer Specific IntegratedCircuit) or ASIC (Application Specific Integrated Circuit) or otherintegrated circuit, a logic circuit, a digital signal processor, aprogrammable logic device such as a FPGA, PLD, PLA or PAL, or any otherdevice or arrangement of devices that is capable of implementing thesteps of the processes of the invention.

The processing machine used to implement the invention may utilize asuitable operating system (OS). Thus, embodiments of the invention mayinclude a processing machine running the Unix operating system, theApple iOS operating system, the Linux operating system, the Xenixoperating system, the IBM AIX™ operating system, the Hewlett-Packard UX™operating system, the Novell Netware™ operating system, the SunMicrosystems Solaris™ operating system, the OS/2™ operating system, theBeOS™ operating system, the Macintosh operating system (such as macOS™),the Apache operating system, an OpenStep™ operating system, the Android™operating system (and variations distributed by Samsung, HTC, Huawei,LG, Motorola, Google, Blackberry, among others), the Windows 10™operating system, the Windows Phone operating system, the Windows 8™operating system, Microsoft Windows™ Vista™ operating system, theMicrosoft Windows™ XP™ operating system, the Microsoft Windows™ NT™operating system, the Windows™ 2000 operating system, or anotheroperating system or platform.

The systems and methods of the invention may utilize non-operatingsystems (aka serverless architecture) as well for distributedprocessing. In the processing of the invention, services on cloudcomputing networks leveraging systems like AWS (as offered by Amazon WebServices, Inc.), BlueMix (as offered by IBM), and Microsoft Azure, canperform data collection services using varying technologies that arespun up on demand using tools like Chef to create container baseddeployments like Docker, or non-container compute services (e.g. AWSLambda).

The invention provides real-time analytics processing that requiresscale on demand to the recipients and users in the system, in accordancewith at least one embodiment of the invention. Such offerings as AWSlambda and Kinesis (as offered by Amazon Web Services, Inc.) are amongthose that may be used in implementation of the invention. For example,AWS Lambda may be utilized to execute code (to perform processes of theinvention) in response to various triggers including data changes,shifts in system state, or particular action taken by recipients andusers. Similarly, in an embodiment, the OS (operating system) of theinvention might be encapsulated in an EC2 instance (as offered by AmazonWeb Services, Inc.) or multiple instances for deployment.

It is appreciated that in order to practice the method of the inventionas described above, it is not necessary that the processors and/or thememories of the processing machine be physically located in the samegeographical place. That is, each of the processors and the memoriesused by the processing machine may be located in geographically distinctlocations and connected so as to communicate in any suitable manner,such as over a network of over multiple networks. Additionally, it isappreciated that each of the processor and/or the memory may be composedof different physical pieces of equipment. Accordingly, it is notnecessary that the processor be one single piece of equipment in onelocation and that the memory be another single piece of equipment inanother location. That is, it is contemplated that the processor may betwo pieces of equipment in two different physical locations. The twodistinct pieces of equipment may be connected in any suitable manner.Additionally, the memory may include two or more portions of memory intwo or more physical locations.

To explain further, processing as described above is performed byvarious components and various memories. However, it is appreciated thatthe processing performed by two distinct components as described abovemay, in accordance with a further embodiment of the invention, beperformed by a single component. Further, the processing performed byone distinct component as described above may be performed by twodistinct components. In a similar manner, the memory storage performedby two distinct memory portions as described above may, in accordancewith a further embodiment of the invention, be performed by a singlememory portion. Further, the memory storage performed by one distinctmemory portion as described above may be performed by two memoryportions.

Further, as also described above, various technologies may be used toprovide communication between the various processors and/or memories, aswell as to allow the processors and/or the memories of the invention tocommunicate with any other entity; i.e., so as to obtain furtherinstructions or to access and use remote memory stores, for example.Such technologies used to provide such communication might include anetwork, the Internet, Intranet, Extranet, LAN, an Ethernet, or anyclient server system that provides communication, for example. Suchcommunications technologies may use any suitable protocol such asTCP/IP, UDP, or OSI, for example.

Further, multiple applications may be utilized to perform the variousprocessing of the invention. Such multiple applications may be on thesame network or adjacent networks, and split between non-cloud hardware,including local (on-premises) computing systems, and cloud computingresources, for example. Further, the systems and methods of theinvention may use IPC (interprocess communication) style communicationfor module level communication. Various known IPC mechanisms may beutilized in the processing of the invention including, for example,shared memory (in which processes are provided access to the same memoryblock in conjunction with creating a buffer, which is shared, for theprocesses to communicate with each other), data records accessible bymultiple processes at one time, and message passing (that allowsapplications to communicate using message queues).

As described above, a set of instructions is used in the processing ofthe invention. The set of instructions may be in the form of a programor software. The software may be in the form of system software orapplication software, for example. The software might also be in theform of a collection of separate programs, a program module within alarger program, or a portion of a program module, for example. Thesoftware used might also include modular programming in the form ofobject oriented programming. The software tells the processing machinewhat to do with the data being processed.

Further, it is appreciated that the instructions or set of instructionsused in the implementation and operation of the invention may be in asuitable form such that the processing machine may read theinstructions. For example, the instructions that form a program may bein the form of a suitable programming language, which is converted tomachine language or object code to allow the processor or processors toread the instructions. That is, written lines of programming code orsource code, in a particular programming language, are converted tomachine language using a compiler, assembler or interpreter. The machinelanguage is binary coded machine instructions that are specific to aparticular type of processing machine, i.e., to a particular type ofcomputer, for example. The computer understands the machine language.

Any suitable programming language may be used in accordance with thevarious embodiments of the invention. Illustratively, the programminglanguage used may include assembly language, Ada, APL, Basic, C, C++,C#, Objective C, COBOL, dBase, Forth, Fortran, Java, Modula-2, Node.JS,Pascal, Prolog, Python, REXX, Visual Basic, and/or JavaScript, forexample. Further, it is not necessary that a single type of instructionsor single programming language be utilized in conjunction with theoperation of the system and method of the invention. Rather, any numberof different programming languages may be utilized as is necessary ordesirable.

Also, the instructions and/or data used in the practice of the inventionmay utilize any compression or encryption technique or algorithm, as maybe desired. An encryption module might be used to encrypt data. Further,files or other data may be decrypted using a suitable decryption module,for example.

As described above, the invention may illustratively be embodied in theform of a processing machine, including a computer or computer system,for example, that includes at least one memory. It is to be appreciatedthat the set of instructions, i.e., the software for example, thatenables the computer operating system to perform the operationsdescribed above may be contained on any of a wide variety of media ormedium, as desired. Further, the data that is processed by the set ofinstructions might also be contained on any of a wide variety of mediaor medium. That is, the particular medium, i.e., the memory in theprocessing machine, utilized to hold the set of instructions and/or thedata used in the invention may take on any of a variety of physicalforms or transmissions, for example. Illustratively, as also describedabove, the medium may be in the form of paper, paper transparencies, acompact disk, a DVD, an integrated circuit, a hard disk, a floppy disk,an optical disk, a magnetic tape, a RAM, a ROM, a PROM, a EPROM, a wire,a cable, a fiber, communications channel, a satellite transmissions orother remote transmission, as well as any other medium or source of datathat may be read by the processors of the invention.

Further, the memory or memories used in the processing machine thatimplements the invention may be in any of a wide variety of forms toallow the memory to hold instructions, data, or other information, as isdesired. Thus, the memory might be in the form of a database to holddata. The database might use any desired arrangement of files such as aflat file arrangement or a relational database arrangement, for example.

In the system and method of the invention, a variety of “recipientinterfaces” or “user interfaces” may be utilized to allow a recipient oruser to interface with the processing machine or machines that are usedto implement the invention. As used herein, a recipient or userinterface includes any hardware, software, or combination of hardwareand software used by the processing machine that allows a recipient oruser to interact with the processing machine. A recipient or userinterface may be in the form of a dialogue screen for example. Arecipient or user interface may also include any of a mouse, touchscreen, keyboard, voice reader, voice recognizer, dialogue screen, menubox, list, checkbox, toggle switch, a pushbutton or any other devicethat allows a recipient or user to receive information regarding theoperation of the processing machine as it processes a set ofinstructions and/or provide the processing machine with information.Accordingly, the recipient or user interface is any device that providescommunication between a recipient or user and a processing machine. Theinformation provided by the recipient or user to the processing machinethrough the recipient or user interface may be in the form of a command,a selection of data, or some other input, for example.

As discussed above, a recipient or user interface is utilized by theprocessing machine that performs a set of instructions such that theprocessing machine processes data for a recipient or user. The recipientor user interface is typically used by the processing machine forinteracting with a recipient or user either to convey information orreceive information from the recipient or user. However, it should beappreciated that in accordance with some embodiments of the system andmethod of the invention, it is not necessary that a human recipient oruser interact with a recipient or user interface used by the processingmachine of the invention. Rather, it is also contemplated that therecipient or user interface of the invention might interact, i.e.,convey and receive information, with another processing machine, ratherthan a human recipient or user. Accordingly, the other processingmachine might be characterized as a recipient or user. Further, it iscontemplated that a recipient or user interface utilized in the systemand method of the invention may interact partially with anotherprocessing machine or processing machines, while also interactingpartially with a human recipient or user.

1. A method for determining a message to send to a recipient devicebased on a selected recipient profile, the method comprising: analyzing,by a system processor, a message stored in a system database todetermine at least one message attribute; analyzing, by the systemprocessor, a plurality of user profiles stored in a profile database todetermine a plurality of user profile attributes; analyzing, by thesystem processor, the at least one message attribute and the pluralityof user profile attributes to identify a user profile from the at leastone user profile for receiving the message, wherein the user profile hasat least one identified attribute and is associated with the recipientdevice; wherein the recipient device has a user profile manager forselecting the selected recipient profile from a plurality of userprofiles on the recipient device; receiving, by the system processor, aset of information on the selected recipient profile; determining, bythe system processor, the selected recipient profile is associated withthe at least one identified attribute; and transmitting, by the systemprocessor, the message to the recipient device.
 2. The method of claim1, the method further including inserting within the message a query fora recipient associated with the recipient device.
 3. The method of claim1, wherein the message is a query.
 4. The method of claim 1, wherein theuser profile matches the selected recipient profile.
 5. The method ofclaim 1, wherein the at least one message attribute is at least onequery attribute and the at least one query attribute is analyzed withthe plurality of user profile attributes.
 6. The method of claim 1, themethod further including holding, by the system processor, the messagefrom being transmitted to the recipient device until the user profilemanager has selected the selected profile having the at least oneidentified attribute.
 7. A system for determining a message to send to arecipient device based on a selected device profile comprising: arelevancy server, the relevancy server including: a relevancy processorincluding instructions on a non-transitory computer medium, thenon-transitory computer medium constituted by at least one data storagemedium; the relevancy processor including a mapping manager module foranalyzing at least one message and a plurality of user profiles toidentify the message to transmit to the recipient device associated withan identified user profile based on the analysis, the identified userprofile coming from the plurality of user profiles; the recipient devicehaving a recipient device processor including a set of recipient deviceinstructions on a recipient device non-transitory computer medium, therecipient device non-transitory computer medium constituted by at leastone recipient device data storage medium; the set of recipient deviceinstructions, when executed by the recipient device processor configurethe recipient device to: select, by a user profile manager on therecipient device, a selected recipient profile from a plurality of userprofiles on the recipient device for the recipient device to use; andtransmit a set of information to the relevancy server on the selectedrecipient profile; the relevancy processor determining the selectedrecipient profile is associated with the at least one identified userprofile; and transmit, by the relevancy processor, the message to therecipient device.
 8. The system of claim 7, further including a queryincluded in the message.
 9. The system of claim 7, wherein the messageis a query.
 10. The system of claim 7, wherein the mapping managermodule analysis includes analyzing at least one message attribute and atleast one user profile attribute from the plurality of user profiles.11. The system of claim 10, wherein the at least one message attributeis a query attribute and the query attribute is analyzed with the atleast one user profile attribute.
 12. The system of claim 7, wherein therelevancy server holds the message from being transmitted to therecipient device until the selected recipient profile selected by theuser profile manager matches the identified user profile.
 13. A systemfor changing a control of a recipient device based on a selectedrecipient profile, the system comprising: a system server, the systemserver including: a system processor including instructions on anon-transitory computer medium, the non-transitory computer mediumconstituted by one or more data storage mediums; the system processorincluding a configuration profile manager module for selecting aselected configuration control profile from a plurality of configurationcontrol profiles based on the selected recipient profile; the recipientdevice having a recipient device processor including a set of recipientdevice instructions on a recipient device non-transitory computermedium, the recipient device non-transitory computer medium constitutedby at least one recipient device data storage medium; the set ofrecipient device instructions, when executed by the recipient deviceprocessor configure the recipient device to: select, by a user profilemanager on the recipient device, a selected recipient profile from aplurality of user profiles on the recipient device; transmit, to thesystem server, a set of information on the selected recipient profile;receive, from the system server, the selected configuration controlprofile based on the selected recipient profile; and adjust the controlon the recipient device based on the selected configuration controlprofile.
 14. The system of claim 13, wherein the control includes abandwidth control for bandwidth usage of the recipient device.
 15. Thesystem of claim 14, the recipient device having a bandwidth manager forcontrolling bandwidth usage and an inter-process communication (IPC)manager for processing communications between the bandwidth manager andthe user profile manager.
 16. The system of claim 13, wherein thecontrol includes a memory control for memory storage of the recipientdevice.
 17. The system of claim 16, the recipient device having astorage manager for controlling the at least one storage medium and aninter-process communication (IPC) manager for processing communicationsbetween the storage manager and the user profile manager.
 18. The systemof claim 13, wherein the control includes a power control for powerconsumption of the recipient device.
 19. The system of claim 18, therecipient device having a power consumption manager for controllingpower consumption and an inter-process communication (IPC) manager forprocessing communications between the power consumption manager and theuser profile manager.
 20. The system of claim 13, wherein the controlincludes a user interface control for the appearance of the userinterface of the recipient device.
 21. The system of claim 20, therecipient device having a user interface manager for controlling theappearance of the user interface and an inter-process communication(IPC) manager for processing communication between the user interfacemanager and the user profile manager.
 22. The system of claim 13, therecipient device having an inter-process communication (IPC) manager forcontrolling the recipient device and for communication with the userprofile manager.
 23. The system of claim 13, wherein the selectedconfiguration control profile is comprised of a set of instructions forcontrolling the recipient device.
 24. The system of claim 13, whereinthe selected configuration control profile is comprised of at least onesetting for controlling the recipient device.